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Update app.py
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app.py
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@@ -5,7 +5,7 @@ import os
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import re
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from PyPDF2 import PdfReader
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# ========== TRANSCRIPT PARSING FUNCTIONS ==========
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def parse_transcript(file):
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if file.name.endswith('.csv'):
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@@ -21,29 +21,62 @@ def parse_transcript(file):
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else:
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return "Unsupported file format", None
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}
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def extract_info_from_pdf(text):
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gpa_match = re.search(r"GPA[:\s]+(\d\.\d+)", text)
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}
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# ========== LEARNING STYLE QUIZ FUNCTION ==========
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@@ -98,7 +131,8 @@ def save_profile(name, age, interests, transcript, learning_style, favorites, bl
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def transcript_display(transcript_dict):
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if not transcript_dict:
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return "No transcript uploaded."
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return "\n".join([f"
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# ========== GRADIO INTERFACE ==========
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with gr.Tab("Step 4: Save & Review"):
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output_summary = gr.Markdown()
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save_btn = gr.Button("Save Profile")
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def gather_and_save(name, age, interests, movie, movie_reason, show, show_reason,
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book, book_reason, character, character_reason, blog, transcript, learning_style):
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favorites = {
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@@ -162,10 +196,4 @@ with gr.Blocks() as app:
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transcript_data, learning_output],
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outputs=output_summary)
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app.launch()
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import re
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from PyPDF2 import PdfReader
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# ========== TRANSCRIPT PARSING FUNCTIONS (UPDATED) ==========
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def parse_transcript(file):
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if file.name.endswith('.csv'):
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else:
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return "Unsupported file format", None
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# Extract GPA (try multiple possible column names)
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gpa = "N/A"
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for col in ['GPA', 'Grade Point Average', 'Cumulative GPA']:
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if col in df.columns:
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gpa = df[col].iloc[0] if isinstance(df[col].iloc[0], (float, int)) else "N/A"
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break
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# Extract grade level (try multiple possible column names)
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grade_level = "N/A"
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for col in ['Grade Level', 'Grade', 'Class', 'Year']:
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if col in df.columns:
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grade_level = df[col].iloc[0]
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break
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# Extract courses (current and past)
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courses = []
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for col in ['Course', 'Subject', 'Course Name', 'Class']:
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if col in df.columns:
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courses = df[col].tolist()
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break
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# Create output display
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output_text = f"Grade Level: {grade_level}\nGPA: {gpa}\n\nCourses:\n"
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output_text += "\n".join(f"- {course}" for course in courses)
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return output_text, {
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"gpa": gpa,
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"grade_level": grade_level,
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"courses": courses
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}
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def extract_info_from_pdf(text):
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# Extract GPA
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gpa_match = re.search(r"(GPA|Grade Point Average)[:\s]+(\d\.\d+)", text, re.IGNORECASE)
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gpa = float(gpa_match.group(2)) if gpa_match else "N/A"
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# Extract grade level
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grade_match = re.search(r"(Grade|Year)[:\s]+(\d+|Freshman|Sophomore|Junior|Senior)", text, re.IGNORECASE)
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grade_level = grade_match.group(2) if grade_match else "N/A"
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# Extract courses - improved pattern to catch more course formats
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course_pattern = r"""
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(?:[A-Z]{2,}\s?\d{3}) # Course codes like 'MATH 101' or 'ENG101'
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|[A-Z][a-z]+(?:\s[A-Z][a-z]+)* # Or full course names
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"""
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courses = re.findall(course_pattern, text, re.VERBOSE)
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courses = list(set(courses)) # Remove duplicates
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# Create output display
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output_text = f"Grade Level: {grade_level}\nGPA: {gpa}\n\nCourses:\n"
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output_text += "\n".join(f"- {course}" for course in courses)
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return output_text, {
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"gpa": gpa,
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"grade_level": grade_level,
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"courses": courses
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}
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# ========== LEARNING STYLE QUIZ FUNCTION ==========
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def transcript_display(transcript_dict):
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if not transcript_dict:
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return "No transcript uploaded."
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return "\n".join([f"- {course}" for course in transcript_dict["courses"]] +
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[f"Grade Level: {transcript_dict['grade_level']}", f"GPA: {transcript_dict['gpa']}"])
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# ========== GRADIO INTERFACE ==========
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with gr.Tab("Step 4: Save & Review"):
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output_summary = gr.Markdown()
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save_btn = gr.Button("Save Profile")
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def gather_and_save(name, age, interests, movie, movie_reason, show, show_reason,
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book, book_reason, character, character_reason, blog, transcript, learning_style):
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favorites = {
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transcript_data, learning_output],
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outputs=output_summary)
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app.launch()
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